CoAuthors

Annabelle Ollivier (CLS, France); Pierre Thibaut (CLS, France); Doug Vandemark (UNH, US); Jean-Damien Desjonqueres (CNES, France)

During the past decade, several studies have focused on the high frequency content of the SSH and its dependence to SWH signal at wavelengths shorter than 100 km. On one hand, Zaron and DeCarvalho [2015] used the observed correlation between the measurement errors of sea-surface height (SSH) and significant wave height (SWH) to correct the SSH data by removing the noise correlated with the SWH noise. This leads to improvements in the signal-to-noise ratio for identification of short-wavelength features, such as the internal tides, with a variance reduction of ~2 cm². On the other hand, spectral analysis of Jason-2 corrections to the range measurements showed that the SSB correction is the dominating signal for wavelength below 100 km and is the only contributor for wavelength below 30 km [Ollivier et al, 2016]. Low-pass filtering the SSB values applied on SSH increases the noise floor of the along-track spectrum when one compares to standard SSB correction application [Ollivier et al, 2008] while 3D SSB solution based on smoothed sigma0, smoothed SWH and the SWH smoothing residual achieves significant variance reduction with respect to standard operational correction. These results altogether point out that the observed variance reductions are likely the result of removing correlation between range measurement noise and SWH measurement noise related to the waveform retracker.
Standard empirical SSB correction encompasses then right physical (e.g., electromagnetic bias, skewness bias, etc.) causes of SWH and SSH correlation but also some retracker-related noise directly linked to the SWH noise. This poster will provide some insight on separate quantification of low-frequency and high-frequency SSB signals to design global SSB correction.